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Wyniki wyszukiwania dla: IMAGE RECOGNITION
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Dependable Integration of Medical Image Recognition Components
PublikacjaComputer driven medical image recognition may support medical doctors in the diagnosis process, but requires high dependability considering potential consequences of incorrect results. The paper presentsa system that improves dependability of medical image recognition by integration of results from redundant components. The components implement alternative recognition algorithms of diseases in thefield of gastrointestinal endoscopy....
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Parameters optimization in medicine supporting image recognition algorithms
PublikacjaIn this paper, a procedure of automatic set up of image recognition algorithms' parameters is proposed, for the purpose of reducing the time needed for algorithms' development. The procedure is presented on two medicine supporting algorithms, performing bleeding detection in endoscopic images. Since the algorithms contain multiple parameters which must be specified, empirical testing is usually required to optimise the algorithm's...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublikacjaIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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Pattern Recognition and Image Analysis
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Automatic Image and Speech Recognition Based on Neural Network
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Blur recognition using second fundamental form of image surface
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Improvement of Image Binarization Methods Using Image Preprocessing with Local Entropy Filtering for Alphanumerical Character Recognition Purposes
PublikacjaAutomatic text recognition from the natural images acquired in uncontrolled lighting conditions is a challenging task due to the presence of shadows hindering the shape analysis and classification of individual characters. Since the optical character recognition methods require prior image binarization, the application of classical global thresholding methods in such case makes it impossible to preserve the visibility of all...
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Fast Statistical Image Binarization of Colour Images for the Recognition of the QR Codes
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Recognition of two-phase flow patterns with the use of dynamic image analysis
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Vehicle type recognition: a case study of MobileNetV2 for an image Classification task
PublikacjaThe goal of the research was to demonstrate the full data science lifecycle through a use case of the MobileNetv2 model for vehicle image Classification task using various validation and test sets, each with different difficulty level. Diverse model variations were employed, each designed to recognize images of ground vehicles and classify them into one of five possible classes: car, truck, motorcycle, bicycle, or bus. In terms...
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Methods of Natural Image Preprocessing Supporting the Automatic Text Recognition Using the OCR Algorithms
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Prediction of the Optical Character Recognition Accuracy based on the Combined Assessment of Image Binarization Results
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Application of Binary Image Quality Assessment Methods to Predict the Quality of Optical Character Recognition Results
PublikacjaOne of the continuous challenges related to the growing popularity of mobile devices and embedded systems with limited memory and computational power is the development of relatively fast methods for real-time image and video analysis. One such example is Optical Character Recognition (OCR), which is usually too complex for such devices. Considering that images captured by cameras integrated into mobile devices may be acquired...
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Application of Binary Image Quality Assessment Methods to Predict the Quality of Optical Character Recognition Results
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International Journal of Signal Processing, Image Processing and Pattern Recognition
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International Conference on Image Analysis and Recognition
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Andrzej Czyżewski prof. dr hab. inż.
OsobyProf. zw. dr hab. inż. Andrzej Czyżewski jest absolwentem Wydziału Elektroniki PG (studia magisterskie ukończył w 1982 r.). Pracę doktorską na temat związany z dźwiękiem cyfrowym obronił z wyróżnieniem na Wydziale Elektroniki PG w roku 1987. W 1992 r. przedstawił rozprawę habilitacyjną pt.: „Cyfrowe operacje na sygnałach fonicznych”. Jego kolokwium habilitacyjne zostało przyjęte jednomyślnie w czerwcu 1992 r. w Akademii Górniczo-Hutniczej...
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A Fast Prediction of the OCR Results Based on Binary Image Quality Assessment Methods
PublikacjaSince the first step of the Optical Character Recognition (OCR) procedure is usually image binarization and the execution of the OCR process takes longer time than image quality assessment (IQA) of binary images, a fast prediction of the OCR results before text recognition would be interesting for non-uniformly illuminated document images, also for applications in mobile devices. Since IQA methods for binary images usually require...
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Human-Computer Interface Based on Visual Lip Movement and Gesture Recognition
PublikacjaThe multimodal human-computer interface (HCI) called LipMouse is presented, allowing a user to work on a computer using movements and gestures made with his/her mouth only. Algorithms for lip movement tracking and lip gesture recognition are presented in details. User face images are captured with a standard webcam. Face detection is based on a cascade of boosted classifiers using Haar-like features. A mouth region is located in...
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Analysis of Image Preprocessing and Binarization Methods for OCR-Based Detection and Classification of Electronic Integrated Circuit Labeling
PublikacjaAutomatic recognition and classification of electronic integrated circuits based on optical character recognition combined with the analysis of the shape of their housings are essential to machine vision methods supporting the production of electronic parts, especially small-volume ones in the through-hole technology, characteristic of printed circuit boards. Since such methods utilize binary images, applying appropriate image...
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Emotion Recognition
Dane BadawczeThe films presented here were recorded using so-called high-speed camera Phantom Miro. To play the movie You need the special software which can be downloaded from the web site https://www.phantomhighspeed.com/resourcesandsupport/phantomresources/pccsoftware the details of the movie are available after starting the movie in the viewer in the description...
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Emotion Recognition
Dane BadawczeThe films presented here were recorded using so-called high-speed camera Phantom Miro. To play the movie You need the special software which can be downloaded from the web site https://www.phantomhighspeed.com/resourcesandsupport/phantomresources/pccsoftware the details of the movie are available after starting the movie in the viewer in the description...
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Comparison of edge detection algorithms for electric wire recognition
PublikacjaEdge detection is the preliminary step in image processing for object detection and recognition procedure. It allows to remove useless information and reduce amount of data before further analysis. The paper contains the comparison of edge detection algorithms optimized for detection of horizontal edges. For comparison purposes the algorithms were implemented in the developed application dedicated to detection of electric line...
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Endoscopic Videos Deinterlacing and On-Screen Text and Light Flashes Removal and Its Influence on Image Analysis Algorithms' Efficiency
PublikacjaIn this article, deinterlacing and removing on- screen text and light flashes methods on endoscopic video images are discussed. The research is intended to improve disease recognition algorithms' performance. In the article, four configurations of deinterlacing methods and another four configurations of text and flashes removal methods are described and examined. The efficiency of endoscopic video analysis algorithms is measured...
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A video monitoring system using ontology-driven identification of threats
PublikacjaIn this paper, we present a video monitoring systemthat leverages image recognition and ontological reasoningabout threats. In the solution, an image processing subsystemuses video recording of a monitored area and recognizesknown concepts in scenes. Then, a reasoning subsystem uses anontological description of security conditions and informationfrom image recognition to check if a violation of a conditionhas occurred. If a threat...
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AN ALGORITHM FOR PORTAL HYPERTENSIVE GASTROPATHY RECOGNITION ON THE ENDOSCOPIC RECORDINGS
PublikacjaSymptoms recognition of portal hypertensive gastropathy (PHG) can be done by analysing endoscopic recordings, but manual analysis done by physician may take a long time. This increases probability of missing some symptoms and automated methods may be applied to prevent that. In this paper a novel hybrid algorithm for recognition of early stage of portal hypertensive gastropathy is proposed. First image preprocessing is described....
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Hand gesture recognition supported by fuzzy rules and Kalman filters
PublikacjaThe paper presents a system based on camera and multimediaprojector enabling a user to control computer applications by dynamic hand gestures. Gesture recognition methodology based on representing hand movement trajectory by motion vectors analysed using fuzzy rule-based inference is first given. For effective hand position tracking Kalman filters are employed. The system engineered is developed using J2SE and C++/OpenCV technology....
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublikacjaRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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Andrzej Stateczny prof. dr hab. inż.
OsobyProf. dr hab. inż. Andrzej Stateczny jest profesorem Politechniki Gdańskiej i prezesem firmy Marine Technology Ltd. Jego zainteresowania naukowe koncentrują się głównie wokół nawigacji, hydrografii i geoinformatyki. Obecnie prowadzone badania obejmują nawigację radarową, nawigację porównawczą, hydrografię, metody sztucznej inteligencji w zakresie przetwarzania obrazów i fuzji danych wielosensorycznych. Był kierownikiem lub głównym...
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Fuzzy rule-based dynamic gesture recognition employing camera & multimedia projector
PublikacjaIn the paper the system based on camera and multimedia projector enabling a user to control computer applications by dynamic hand gestures is presented. The main objective is to present the gesture recognition methodology which bases on representing hand movement trajectory by motion vectors analyzed using fuzzy rule-based inference. The approach was engineered in the system developed with J2SE and C++ / OpenCV technology. OpenCV...
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A method supporting fault-tolerant optical text recognition from video sequences recorded with handheld cameras
PublikacjaIn the paper a method supporting the optical character recognition from video sequences recorded with cameras without good stabilization is proposed. Due to the presence of various distortions, such as motion blur, shadows, lossy compression artifacts, auto-focusing errors, etc., the quality of individual video frames, e.g., recorded by a smartphone camera, differs noticeably, influencing the results of text recognition, causing...
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Examining Classifiers Applied to Static Hand Gesture Recognition in Novel Sound Mixing System
PublikacjaThe main objective of the chapter is to present the methodology and results of examining various classifiers (Nearest Neighbor-like algorithm with non-nested generalization (NNge), Naive Bayes, C4.5 (J48), Random Tree, Random Forests, Artificial Neural Networks (Multilayer Perceptron), Support Vector Machine (SVM) used for static gesture recognition. A problem of effective gesture recognition is outlined in the context of the system...
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Normalization of face illumination using basic knowledge and information extracted from a single image
PublikacjaThis paper presents a method for face image normalization that can be applied to the extraction of illumination invariant facial features or used to remove bad lighting effects and produce high-quality, photorealistic results. Most of the existing approaches concentrate on separating the constant albedo from the variable light intensity; that concept, however, is based on the Lambertian model, which fails in the presence of specularities...
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Wykorzystanie sztucznych sieci neuronowych do wykrywania i rozpoznawania tablic rejestracyjnych na zdjęciach pojazdów
PublikacjaW artykule przedstawiono koncepcję algorytmu wykrywania i rozpoznawania tablic rejestracyjnych (AWiRTR) na obrazach cyfrowych pojazdów. Detekcja i lokalizacja tablic rejestracyjnych oraz wyodrębnienie z obrazu tablicy rejestracyjnej poszczególnych znaków odbywa się z wykorzystaniem podstawowych technik przetwarzania obrazu (przekształcenia morfologiczne, wykrywanie krawędzi) jak i podstawowych danych statystycznych obiektów wykrytych...
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Scoreboard Architectural Pattern and Integration of Emotion Recognition Results
PublikacjaThis paper proposes a new design pattern, named Scoreboard , dedicated for applications solving complex, multi-stage, non-deterministic problems. The pattern provides a computational framework for the design and implementation of systems that integrate a large number of diverse specialized modules that may vary in accuracy, solution level, and modality. The Scoreboard is an extension of Blackboard design pattern and comes under...
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EXAMINING INFLUENCE OF VIDEO FRAMERATE AND AUDIO/VIDEO SYNCHRONIZATION ON AUDIO-VISUAL SPEECH RECOGNITION ACCURACY
PublikacjaThe problem of video framerate and audio/video synchronization in audio-visual speech recognition is considered. The visual features are added to the acoustic parameters in order to improve the accuracy of speech recognition in noisy conditions. The Mel-Frequency Cepstral Coefficients are used on the acoustic side whereas Active Appearance Model features are extracted from the image. The feature fusion approach is employed. The...
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IMAGE CORRELATION AS A TOLL FOR TRACKING FACIAL CHANGES CAUSING BY EXTERNAL STIMULI
PublikacjaExpressions of the human face bring a lot of information, which are a valuable source in the areas of computer vision, remote sensing and affective computing. For years, by analyzing the movement of the skin and facial muscles scientists are trying to create the perfect tool, based on image analysis, allowing the recognition of emotional states of human beings. To create a reliable algorithm, it is necessary to explore and examine...
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EXAMINING INFLUENCE OF VIDEO FRAMERATE AND AUDIO/VIDEO SYNCHRONIZATION ON AUDIO-VISUAL SPEECH RECOGNITION ACCURACY
PublikacjaThe problem of video framerate and audio/video synchronization in audio-visual speech recogni-tion is considered. The visual features are added to the acoustic parameters in order to improve the accuracy of speech recognition in noisy conditions. The Mel-Frequency Cepstral Coefficients are used on the acoustic side whereas Active Appearance Model features are extracted from the image. The feature fusion approach is employed. The...
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Automatic Watercraft Recognition and Identification on Water Areas Covered by Video Monitoring as Extension for Sea and River Traffic Supervision Systems
PublikacjaThe article presents the watercraft recognition and identification system as an extension for the presently used visual water area monitoring systems, such as VTS (Vessel Traffic Service) or RIS (River Information Service). The watercraft identification systems (AIS - Automatic Identification Systems) which are presently used in both sea and inland navigation require purchase and installation of relatively expensive transceivers...
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Robust unsupervised georeferencing algorithm for aerial and satellite imagery
PublikacjaIn order to eliminate a human factor and fully automate the process of embedding the spatial localization information in a remote sensed image the integrated georeferencing method was proposed. The paper presents this unsupervised and robust approach which is comprised of pattern recognition, using SIFT-based detector, and RANSAC based outlier removal with matching algorithm.
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Potential and Use of the Googlenet Ann for the Purposes of Inland Water Ships Classification
PublikacjaThis article presents an analysis of the possibilities of using the pre-degraded GoogLeNet artificial neural network to classify inland vessels. Inland water authorities monitor the intensity of the vessels via CCTV. Such classification seems to be an improvement in their statutory tasks. The automatic classification of the inland vessels from video recording is a one of the main objectives of the Automatic Ship Recognition and...
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Superresolution algorithm to video surveillance system
PublikacjaAn application of a multiframe SR (superresolution) algorithm applied to video monitoring is described. The video signal generated by various types of video cameras with different parameters and signal distortions which may be very problematic for superresolution algorithms. The paper focuses on disadvantages in video signal which occur in video surveillance systems. Especially motion estimation and its influence on superresolution...
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Analysis of the objects images on the sea using Dempster-Shafer Theory
PublikacjaThe paper presents the concept of using aerial and satellite imagery or images coming from the marine radar to identify and track vessels at sea. The acquired data were subjected to a highly advanced image analysis. The development of remote sensing techniques allows to gain a huge amount of data. These data are useful information source however usually we have to use different data mining methods to gain interested information....
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Using Different Information Channels for Affect-Aware Video Games - A Case Study
PublikacjaThis paper presents the problem of creating affect-aware video games that use different information channels, such as image, video, physiological signals, input devices, and player’s behaviour, for emotion recognition. Presented case studies of three affect-aware games show certain conditions and limitations for using specific signals to recognize emotions and lead to interesting conclusions.
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The Hough transform in the classification process of inland ships
PublikacjaThis article presents an analysis of the possibilities of using image processing methods for feature extraction that allows kNN classification based on a ship’s image delivered from an on-water video surveillance system. The subject of the analysis is the Hough transform which enables the detection of straight lines in an image. The recognized straight lines and the information about them serve as features in the classification...
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Comparison of Tracking Methods in Respect of Automation of Animal Behavioral Test
PublikacjaAutomation in experiments carried out on animals is getting more and more important in research. Computers take over laborious and time-consuming activities like recording and analysing images of experiment scene. The first step in an image analysis is finding and distinguishing between the observed animals, and then tracking all objects during the experiment. In this paper four tracking methods are presented. Quantitative and...
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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublikacjaHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
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Combined Single Neuron Unit Activity and Local Field Potential Oscillations in a Human Visual Recognition Memory Task
PublikacjaGOAL: Activities of neuronal networks range from action potential firing of individual neurons, coordinated oscillations of local neuronal assemblies, and distributed neural populations. Here, we describe recordings using hybrid electrodes, containing both micro- and clinical macroelectrodes, to simultaneously sample both large-scale network oscillations and single neuron spiking activity in the medial temporal lobe structures...